Yuyan Ge

My goal is to become a bridge between engineering and medicine.

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Hi there!

My name is Yuyan Ge (鬲雨妍). I am currently a PhD student in Computer and Information Science at the University of Pennsylvania (Penn), advised by Prof. René Vidal. I also collaborate closely with Prof. Julio Chirinos at the Perelman School of Medicine at Penn, which allows me to ground my methodological research in real medical problems.

Before joining Penn, I received my Master’s degree in Control Science and Engineering from Xi’an Jiaotong University (XJTU), advised by Prof. Shaoyi Du. I received my Bachelor’s degree in Automation from XJTU. During my Master’s, I was a visiting student in the IDEA Lab at ShanghaiTech University, advised by Prof. Dinggang Shen.

My research interests lie in machine learning and medical image analysis, with a focus on developing interpretable and reliable AI methods for healthcare.

Recent News

May 09, 2026 Gave an Oral presentation on Cardiovascular Age at NAA 2026!
Apr 30, 2026 Volunteering at IDEAS on Generative AI Symposium at Penn!
Apr 17, 2026 Presenting our work IP-CRR and EchoRG at AI in Medicine Symposium at Penn!
Mar 16, 2026 Our work on Cardiovascular Age Assessment is accepted by NAA 2026 as an Oral presentation!
Mar 11, 2026 Our paper BrainParc is published online in Nature Computational Science!
Mar 06, 2026 Our paper SonoYOLO + MedSAM2 is selected as an Oral presentation at ISBI 2026!
Feb 04, 2026 Passed my Research Qualifier! Thanks to my committee: Prof. James Gee, Prof. Kevin Johnson, and Prof. René Vidal.
Nov 30, 2025 Attending RSNA 2025 in Chicago, Nov. 30 – Dec. 4.
Oct 10, 2025 Volunteering at PennAI Symposium at Penn, Oct. 10 – 11!
Sep 18, 2025 Our paper C-IP is accepted by NeurIPS 2025!
Aug 11, 2025 Volunteering at CoLLAs 2025 at Penn, Aug. 11 – 14!
Jul 14, 2025 Our paper CXR-LT 2024 is accepted by Medical Image Analysis!

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Selected Publications

  1. Assessment of Cardiovascular Age from Echocardiography Using Deep Learning
    Yuyan Ge, Hamed Tavolinejad, Mateo Sarmiento Bustamante, Benjamin Haeffele, René Vidal*, and Julio Chirinos*
    In North American Artery (NAA) Annual Conference, 2026
    Oral Abstract
  2. BrainParc: Unified Lifespan Brain Parcellation from Structural MR Images
    Jiameng Liu, Feihong Liu, Kaicong Sun, Zhiming Cui, Tianyang Sun, Zehong Cao, Jiawei Huang, Shuwei Bai, Yulin Wang, Yulong Dou, Kaicheng Zhang, Caiwen Jiang, Yuyan Ge, Han Zhang, Feng Shi*, and Dinggang Shen*
    Nature Computational Science, 2026
  3. SonoYOLO + MedSAM2: A Pipeline for Automatic Detection and Segmentation of Regions of Interest in Cardiac Ultrasound Videos
    Iraj Shroff, Yuyan Ge*, and René Vidal*
    In IEEE International Symposium on Biomedical Imaging (ISBI), 2026
    Oral presentation
  4. Conformal Information Pursuit for Interactively Guiding Large Language Models
    Kwan Ho Ryan Chan*, Yuyan Ge, Edgar Dobriban, Hamed Hassani, and René Vidal
    In Advances in Neural Information Processing Systems (NeurIPS), 2025
  5. IP-CRR: Information Pursuit for Interpretable Classification of Chest Radiology Reports
    Yuyan Ge*, Kwan Ho Ryan Chan, Pablo Messina, and René Vidal
    In Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2025
  6. CXR-LT 2024: A MICCAI Challenge on Long-Tailed, Multi-Label, and Zero-Shot Disease Classification from Chest X-ray
    Mingquan Lin, Gregory Holste, Song Wang, Yiliang Zhou, Yishu Wei, Imon Banerjee, Pengyi Chen, Tianjie Dai, Yuexi Du, Nicha C. Dvornek, Yuyan Ge, Zuwei Guo, Shouhei Hanaoka, Dongkyun Kim, Pablo Messina, Yang Lu, Denis Parra, Donghyun Son, Álvaro Soto, Aisha Urooj, René Vidal, Yosuke Yamagishi, Pingkun Yan, Zefan Yang, Ruichi Zhang, Yang Zhou, Leo Anthony Celi, Ronald M. Summers, Zhiyong Lu, Hao Chen, Adam E. Flanders, George Shih, Zhangyang Wang*, and Yifan Peng*
    Medical Image Analysis, 2025
    Includes our 1st-place zero-shot classification entry
  7. Multi-Scale and Focal Region Based Deep Learning Network for Fine Brain Parcellation
    Yuyan Ge, Zhenyu Tang, Lei Ma, Caiwen Jiang, Feng Shi, Shaoyi Du*, and Dinggang Shen*
    In MICCAI Workshop on Machine Learning in Medical Imaging (MLMI), 2022
    Oral presentation

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